Maximal nowhere dense PP-sets in basically disconnected spaces and FF-spaces

summary:In [5] the following question was put: are there any maximal n.d. sets in $\omega^*$? Already in [9] the negative answer (under {\bf MA}) to this question was obtained. Moreover, in [9] it was shown that no $P$-set can be maximal n.d. In the present paper the notion of a maximal n.d. $P$-set is introduced and it is proved that under {\bf CH} there is no such a set in $\omega^*$. The main results are Theorem 1.10 and especially Theorem 2.7(ii) (with Example in Section 3) in which the problem of the existence of maximal n.d. $P$-sets in basically disconnected compact spaces with rich families of n.d. $P$-sets is actually solved

Radiation Pressure Dominate Regime of Relativistic Ion Acceleration

The electromagnetic radiation pressure becomes dominant in the interaction of the ultra-intense electromagnetic wave with a solid material, thus the wave energy can be transformed efficiently into the energy of ions representing the material and the high density ultra-short relativistic ion beam is generated. This regime can be seen even with present-day technology, when an exawatt laser will be built. As an application, we suggest the laser-driven heavy ion collider.Comment: 10 pages, 4 figure

Tunable high-energy ion source via oblique laser pulse incidence on a double-layer target

The laser-driven acceleration of high quality proton beams from a double-layer target, comprised of a high-Z ion layer and a thin disk of hydrogen, is investigated with three-dimensional particle-in-cell simulations in the case of oblique incidence of a laser pulse. It is shown that the proton beam energy reaches its maximum at a certain incidence angle of the laser pulse, where it can be much greater than the energy at normal incidence. The proton beam propagates at some angle with respect to the target surface normal, as determined by the proton energy and the incidence angle

Autoresonance in a Dissipative System

We study the autoresonant solution of Duffing's equation in the presence of dissipation. This solution is proved to be an attracting set. We evaluate the maximal amplitude of the autoresonant solution and the time of transition from autoresonant growth of the amplitude to the mode of fast oscillations. Analytical results are illustrated by numerical simulations.Comment: 22 pages, 3 figure

Temperature dependence of plasmonic terahertz absorption in grating-gate gallium-nitride transistor structures

Strong plasmon resonances have been observed in the terahertz transmission spectra (1-5 THz) of large-area slit-grating-gate AlGaN/GaN-based high-electron-mobility transistor (HEMT) structures at temperatures from 10 to 170 K. The resonance frequencies correspond to the excitation of plasmons with wave vectors equal to the reciprocal lattice vectors of the metal grating, which serves both as a gate electrode for the HEMT and a coupler between plasmons and incident terahertz radiation. Wide tunability of the resonances by the applied gate voltage demonstrates potential of these devices for terahertz applications

In-Line-Test of Variability and Bit-Error-Rate of HfOx-Based Resistive Memory

Spatial and temporal variability of HfOx-based resistive random access memory (RRAM) are investigated for manufacturing and product designs. Manufacturing variability is characterized at different levels including lots, wafers, and chips. Bit-error-rate (BER) is proposed as a holistic parameter for the write cycle resistance statistics. Using the electrical in-line-test cycle data, a method is developed to derive BERs as functions of the design margin, to provide guidance for technology evaluation and product design. The proposed BER calculation can also be used in the off-line bench test and build-in-self-test (BIST) for adaptive error correction and for the other types of random access memories.Comment: 4 pages. Memory Workshop (IMW), 2015 IEEE Internationa

Glutamate-mediated blood-brain barrier opening. implications for neuroprotection and drug delivery

The blood-brain barrier is a highly selective anatomical and functional interface allowing a unique environment for neuro-glia networks. Blood-brain barrier dysfunction is common in most brain disorders and is associated with disease course and delayed complications. However, the mechanisms underlying blood-brain barrier opening are poorly understood. Here we demonstrate the role of the neurotransmitter glutamate in modulating early barrier permeability in vivo Using intravital microscopy, we show that recurrent seizures and the associated excessive glutamate release lead to increased vascular permeability in the rat cerebral cortex, through activation of NMDA receptors. NMDA receptor antagonists reduce barrier permeability in the peri-ischemic brain, whereas neuronal activation using high-intensity magnetic stimulation increases barrier permeability and facilitates drug delivery. Finally, we conducted a double-blind clinical trial in patients with malignant glial tumors, using contrast-enhanced magnetic resonance imaging to quantitatively assess blood-brain barrier permeability. We demonstrate the safety of stimulation that efficiently increased blood-brain barrier permeability in 10 of 15 patients with malignant glial tumors. We suggest a novel mechanism for the bidirectional modulation of brain vascular permeability toward increased drug delivery and prevention of delayed complications in brain disorders. SIGNIFICANCE STATEMENT: In this study, we reveal a new mechanism that governs blood-brain barrier (BBB) function in the rat cerebral cortex, and, by using the discovered mechanism, we demonstrate bidirectional control over brain endothelial permeability. Obviously, the clinical potential of manipulating BBB permeability for neuroprotection and drug delivery is immense, as we show in preclinical and proof-of-concept clinical studies. This study addresses an unmet need to induce transient BBB opening for drug delivery in patients with malignant brain tumors and effectively facilitate BBB closure in neurological disorders

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

GRMA: Generalized Range Move Algorithms for the efficient optimization of MRFs

Markov Random Fields (MRF) have become an important tool for many vision applications, and the optimization of MRFs is a problem of fundamental importance. Recently, Veksler and Kumar et al. proposed the range move algorithms, which are some of the most successful optimizers. Instead of considering only two labels as in previous move-making algorithms, they explore a large search space over a range of labels in each iteration, and significantly outperform previous move-making algorithms. However, two problems have greatly limited the applicability of range move algorithms: 1) They are limited in the energy functions they can handle (i.e., only truncated convex functions); 2) They tend to be very slow compared to other move-making algorithms (e.g., �-expansion and ��-swap). In this paper, we propose two generalized range move algorithms (GRMA) for the efficient optimization of MRFs. To address the first problem, we extend the GRMAs to more general energy functions by restricting the chosen labels in each move so that the energy function is submodular on the chosen subset. Furthermore, we provide a feasible sufficient condition for choosing these subsets of labels. To address the second problem, we dynamically obtain the iterative moves by solving set cover problems. This greatly reduces the number of moves during the optimization.We also propose a fast graph construction method for the GRMAs. Experiments show that the GRMAs offer a great speedup over previous range move algorithms, while yielding competitive solutions